I used the gstat package to interpolate measurements of eight environmental
variables in a square 15.4 m x 15.4 m, and then I used model selection from
another package to build models of dependence of plant population locations on
those environmental variables. I used the idw() function to interpolate the
environmental variables. The model selection procedure defined which of the
eight variables helped to explain the patterns seen in my plant populations.
Are there any guidelines for the choice of the inverse distance weighting power
(idp)? I had been using idp=2, because it was the default, but for some
variables it made the surface look not very smooth. I have tried my models on
surfaces with other values of idp, and changing this parameter causes the model
selection procedure to arrive at different models.
Does anyone have any advice or guidelines about the choice of the ipd
parameter, other than "tweaking" it until the surfaces look smooth?
Thank you,
Erika Mudrak
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